More details for the model transformation.
Similar to other experiments on small-size datasets, we use a small batch size of 8 to guarantee enough training iterations on Cityscapes. Sparse RCNN is trained with focal loss [1]} and 300 queries, under the same data augmentation pipeline as DETR.
